根据对该算法的目标状态估计误差分析结果，文中给出了一种误差补偿方法。
Based on the results of target state estimation error analyzing of this algorithm, this paper gives out an error compensation method.
实验结果表明，它是足够的，只使用节点上的信息具有较高的本地SNR为目标状态估计。
Experimental results demonstrate that it is sufficient to only use the information on nodes with higher local SNR for target state estimation.
围绕被动导引头跟踪过程中目标辐射源信号丢失的问题，提出一种基于目标状态估计的抗目标信号丢失方法。
For the problem of loss of target signal during target tracking in passive seeker, a new method is presented for anti-loss of target signal based on target state estimation.
为解决目标跟踪精度与观测时间间隔的矛盾，提出了一种基于目标状态估计协方差控制的观测时间确定算法。
To solve the contradiction between target tracking accuracy and observation interval, an algorithm of calculating observation time based on target estimate covariance control was presented.
为了提高在杂波环境下跟踪强机动目标的精度，提出了一种新的基于期望极大化(EM)算法的机动目标状态估计方法。
To improve the accuracy of tracking the complex maneuver target in cluttered environment, a new state estimation algorithm based on the expectation maximization (EM) algorithm is presented.
数据关联和目标状态估计两部分既有一定的独立性又有密切的联系，而将两部分合理地结合对提高跟踪系统的性能是重要的。
The data correlation and state estimation are both certainly independent and closely relative, but the performance of tracking systems can be improved by suitable incorporating the two components.
为了能够有效地估计目标运动状态，选择适当测度集合是第一步。
In order to extract target states more effectively, choosing appropriately measurement set is the first thing.
本文指出了数据融合中最为关键的几个问题——数据关联、状态估计和目标识别并围绕它们进行了深入的研究。
This dissertation points out the most pivotal problems in data fusion, i. e., data association, state estimation and target recognition, which are investigated in depth.
该算法利用伪测量值，将非线性测量方程变为线性伪测量方程，实现对目标状态的实时估计。
This algorithm makes use of the pseudo measurements to change the nonlinear measurement equation to pseudo linear one, realizing the real-time estimation of target states.
在估计目标状态时，采用了粒子滤波算法，设计了基于自适应表面模型的观测模型；
When estimating the target state, particle filter is adopted, and the observation model is designed based on the adaptive appearance model.
基于多传感器多模型信息，给出了目标状态基于全局信息融合估计的一种新算法，并通过计算机仿真验证了这种算法的有效性。
Based on Multi_sensor Multi_model information, we present a new algorithm based on total information fusion estimation on target state. We prove the validity of this algorithm by computer.
这两种方法的共同点是都是通过建立目标运动的参数模型，获得目标的运动状态估计，从而实现目标跟踪。
Both tracking methods achieve the target tracking state in common by establishing the motion parameter model and obtaining the motion state estimation of the target.
另一类在估计目标状态时并没有利用数据融合。
The other estimates target state without explicit use of a data association algorithm.
通过计算系统可观测度和采用无迹卡尔曼滤波(ukf)对目标相对运动状态进行估计，研究了观测矢量方向和数量与相对导航精度的关系。
System observability matrix was derived, and the degree of observability was calculated. Relative motion states of non-cooperative space target were estimated through unscented Kalman filter (UKF).
采用卡尔曼滤波器对目标进行跟踪时，目标初始状态估计是影响初始阶段跟踪精度的一个重要原因。
When using Kalman Filter to track a target, estimation of the initial state of the target is an important factor influencing tracking precision in the initial phase.
利用这些估计值可以完成对目标的距离跟踪、成像、状态的预测以及动目标指示等过程。
By using these estimation values, the range tracking, profile, status forecasting and MTI (Moving Target Indication) process can be realized.
最后，在顺序得到本周期内各个观测点处目标估计值的同时，也将获得下一时刻目标状态基于全局信息的估计值或预测估计值。
Finally, the next state estimate or predicted estimate may be got by global information after all state estimates relative to all observation point in this period have been obtained in turn.
深入研究了多传感器数据融合的理论方法，并实验研究了数据融合的估计理论在光电经纬仪中的应用，目的是实现对目标状态的预测。
The theory method of multi-sensor data fusion is studied deep. And more, the estimate theory of data fusion is applied concretely to the theodolite with the aim of prognosticating the object state.
该算法不需要假定目标的机动加速度模型，而是直接正确地估计出机动目标的当前状态，不存在任何估计滞后与修正问题。
With the algorithm, the current state of maneuvering target can be estimated directly and correctly without assuming the model of maneuvering acceleration.
目标通过对自身和导弹的状态估计，估计出相对导弹作不同机动时所获得的效能，并以最大效能为最优机动形式。
By estimating the state of a missile, the efficiency of object maneuvering is gained, and the highest efficiency is taken as the optimized maneuvering.
本文主要研究了红外成像应用系统中的目标跟踪问题，重点对目标跟踪的状态估计、跟踪起始、维持和终结等进行了研究。
The subject of the target tracking in the infrared alarm system has been studied in this paper, focusing on the state estimation, tracking start, maintain and tracking termination.
可以通过分析估计看状态模型是否达到想要的目标。
State machines can be analytically evaluated as to whether or not they meet the desired goals.
该算法可以有效地实现异类传感器之间的误差配准，同时估计目标的运动状态和传感器的系统误差。
Registration for heterogeneous sensor can be realized effectively, track of target and sensors' systematic errors can be estimated simultaneously.
由于选择了新的机动加速度量，从而得出线性的状态方程，由机动指令的实时估计得到机动目标自适应跟踪卡尔曼滤波器。
A linear state equation is got from selection of maneuvering acceleration. The adaptivity of adaptive tracking Kalman filter is represented by estimation of maneuvering commander at real time.
目标的观测和状态估计涉及目标的各种运动和属性数据，其中位置不确定性是最重要的性能指标。
The measurement and state estimation of targets involves kinematics and attribute data, in which positional uncertainty is of the most important performance.
用UK -GMPHDF完成局部传感器的局部状态估计，然后用FCM算法对这些局部状态进行融合处理，产生目标的全局状态估计。
In the algorithm, the UK-GMPHDF is used to complete local state estimation of local sensors, then the FCM algorithm is used to fuse the local state estimation and result global state estimation.
基于此模型，可定量地分析引入PMU以后对状态估计精度的改善程度。进而讨论了以提高状态估计精度为目标的PMU配置方案。
Based on the model, the precision improvement of state estimation due to incorporation of PMUs can be analyzed quantitatively and the scheme of PMU placement can be established.
基于此模型，可定量地分析引入PMU以后对状态估计精度的改善程度。进而讨论了以提高状态估计精度为目标的PMU配置方案。
Based on the model, the precision improvement of state estimation due to incorporation of PMUs can be analyzed quantitatively and the scheme of PMU placement can be established.
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